Zerynth Glossary
Explore our Glossary page for Industry 4.0, and AI terms. Discover the key to understanding cutting-edge technologies.
Zerynth Glossary
Explore our Glossary page for Industry 4.0, and AI terms. Discover the key to understanding cutting-edge technologies.
Industry 4.0 manufacturing, also known as Manufacturing 4.0 or Factory 4.0, refers to the integration of advanced Industry 4.0 technologies like IoT, AI, and robotics into manufacturing. It revolutionizes the industry by creating interconnected and automated factories, optimizing processes, improving productivity, and enabling real-time data exchange. It represents the fourth industrial revolution, transforming traditional manufacturing into smart, efficient, and data-driven systems.
IoT based predictive maintenance, also known as maintenance 4.0, refers to the use of predictive maintenance software and Internet of Things (IoT) technologies to optimize maintenance processes in industrial settings. By leveraging real-time data from sensors and other IoT devices, predictive maintenance software can identify potential equipment failures before they occur, allowing for proactive maintenance and reducing downtime and costs.
Condition monitoring involves the continuous tracking of equipment’s operational status. This strategy allows companies to monitor equipment health, detect anomalies, and predict failures, all of which contribute to improved efficiency and productivity.
The concept of machine health refers to the overall condition of a machine in terms of operational efficiency, reliability, and ability to function without failures or malfunctions. It is assessed through parameters such as vibrations, temperature, noise, and energy consumption.
Industrial energy efficiency refers to the optimization of energy use and reduction of waste in industrial processes, it could be achieved through the use of energy monitoring software and IoT power consumption sensors.
Process quality refers to the ability of a production process to consistently deliver outcomes that meet specific requirements and expectations by minimizing variability and delays. It’s a critical concept in quality management, measured by the process’s effectiveness, meaning its ability to operate within set timeframes while achieving the best results in accordance with predefined standards.
Industrial IoT platform refers to the use of IoT to improve production efficiency in Industry. It can collect real-time data on machines, processes, and workers, allowing for more efficient and effective production management. Industrial IoT applications can include predictive maintenance, quality control, supply chain management, energy management etc. Benefits are improving production efficiency, reducing waste, and increasing profitability.
Industrial IoT applications refer to the various use cases and implementations of Internet of Things (IoT) technologies in industrial settings. Industrial IoT platforms are software frameworks that enable the integration and management of IoT devices, data, and applications in an industrial context. IoT can improve production efficiency by leveraging real-time data and analytics from IoT devices.
Industrial IoT refers to the application of IoT technologies and IoT software within the context of Industry 4.0, enabling the connection of industrial devices, sensors, and machinery to gather real-time data for improving efficiency and strategic decision-making.
An energy monitoring system is a technological solution that allows real-time monitoring of power consumption in order to achieve industrial energy efficiency, by identifying inefficiencies and adopting energy-saving measures.
Achieving production optimization means identifying and resolving inefficiencies in manufacturing processes. Employing production monitoring technologies allows for pinpointing inefficiencies while gaining visibility with production tracking.
IoT technology refers to a network of physical devices, vehicles, appliances, and other objects embedded with sensors, software, and connectivity capabilities.